scholarly journals A Lubricating Oil Condition Monitoring System Based on Wear Particle Kinematic Analysis in Microfluid for Intelligent Aeroengine

Micromachines ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 748
Author(s):  
Zhenzhen Liu ◽  
Yan Liu ◽  
Hongfu Zuo ◽  
Han Wang ◽  
Hang Fei
Keyword(s):  
Condition Monitoring ◽  
Kinematic Analysis ◽  
Oil Quality ◽  
Particle Diameter ◽  
Wear Particle ◽  
Lubricating Oil ◽  
Wear Particles ◽  
Oil Viscosity ◽  
Monitoring Technology ◽  
Oil Monitoring

Lubricating oil monitoring technology is a commonly used method in aeroengine condition monitoring, which includes particle counting technology, as well as spectral and ferrography technology in offline monitoring. However, these technologies only analyze the characteristics of wear particles and rely on physical and chemical analysis techniques to monitor the oil quality. In order to further advance offline monitoring technology, this paper explores the potential role of differences in wear particle kinematic characteristics in recognizing changes in wear particle diameter and oil viscosity. Firstly, a kinematic force analysis of the wear particles in the microfluid was carried out. Accordingly, a microfluidic channel conducive to observing the movement characteristics of particles was designed. Then, the wear particle kinematic analysis system (WKAS) was designed and fabricated. Secondly, a real-time tracking velocity measurement algorithm was developed by using the Gaussian mixture model (GMM) and the blob-tracking algorithm. Lastly, the WKAS was applied to a pin–disc tester, and the experimental results show that there is a corresponding relationship between the velocity of the particles and their diameter and the oil viscosity. Therefore, WKAS provides a new research idea for intelligent aeroengine lubricating oil monitoring technology. Future work is needed to establish a quantitative relationship between wear particle velocity and particle diameter, density, and oil viscosity.

Field-Testing of Biodiesel (B100) and Diesel-Fueled Vehicles: Part 2—Lubricating Oil Condition Monitoring

2020 ◽  
Vol 143 (4) ◽  
Author(s):  
Avinash Kumar Agarwal ◽  
Deepak Agarwal
Keyword(s):  
Thermal Stability ◽  
Trace Metal ◽  
Condition Monitoring ◽  
Direct Injection ◽  
Field Testing ◽  
Ash Content ◽  
Operating Conditions ◽  
Lubricating Oil ◽  
Base Number ◽  
Oil Viscosity

Abstract This study investigated the use of biodiesel (B100) and baseline diesel in two identical unmodified vehicles to realistically assess different aspects of biodiesel’s compatibility with modern common rail direct injection (CRDI) diesel engines and its effects on lubricating oil degradation and wear. Two identical vehicles were operated for 30,000 km each under identical operating conditions on highway during a field-trial while using biodiesel (B100) and baseline mineral diesel. Exhaustive experimental results from this series of tests were divided into four segments, and this paper covers the second segment showing the effect of long-term usage of biodiesel on the lubricating oil properties and traces of wear metal addition compared to baseline mineral diesel. Lubricating oil samples were drawn periodically from these vehicles for condition monitoring such as lubricating oil viscosity, density, soot content, total base number (TBN), ash content, trace metal concentrations, and thermal stability. The viscosity of lubricating oil samples drawn from biodiesel fueled vehicles were found to be ∼10–15% lower compared to that from diesel-fueled vehicles, whereas density and ash content were relatively lower by ∼5–10%. Carbon residues of lubricating oil samples drawn from B100 fueled vehicles were lower by ∼15–20% compared to that of diesel-fueled vehicles. There was a very strong reduction (∼70%) in the soot content of lubricating oil from biodiesel fueled vehicles. Trace metal analysis to compare wear debris addition was also done for all lubricating oil samples. Thermo-gravimetric analyses of lubricating oil samples from biodiesel fueled vehicles showed lower mass loss with increasing temperature hence relatively higher thermal stability and lower deterioration. Results also suggested that operational and durability issues associated with vegetable oils as alternate fuel were completely eliminated by using them after converting them into biodiesel meeting prevailing biodiesel specifications.

On-Line Oil Condition Monitoring System

2013 ◽  
Vol 475-476 ◽  
pp. 7-11 ◽  
Author(s):  
Xin Yuan Liang
Keyword(s):  
Monitoring System ◽  
Condition Monitoring ◽  
Basic Research ◽  
Lubricating Oil ◽  
Oil Condition Monitoring ◽  
Computer Image Processing ◽  
On Line ◽  
Condition Monitoring System ◽  
New Research ◽  
Oil Monitoring

An on-line monitoring system was proposed to monitor lubrication oil real-time condition. Oil is the machine equipment blood, and its condition has very serious influence on machine running. Firstly, this paper expiated the research significance of on-line oil monitoring. Then the key problem of on-line oil monitoring was discussed and its goal was analyzed. Furthermore, basic research content and research thread were put forward. Based on the modern photoelectric detection, microscopic imaging and computer image processing technology, an on-line acquisition system of lubricating oil particle image was proposed. This work provides a new research idea for on-line monitoring system which is important to develop the technology of oil condition monitoring.

scholarly journals Research Progress on Monitoring and Separating Suspension Particles for Lubricating Oil

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Ziping Wang ◽  
Xian Xue ◽  
He Yin ◽  
Zhengxuan Jiang ◽  
Yefei Li
Keyword(s):  
High Efficiency ◽  
Suspended Particles ◽  
Research Progress ◽  
Lubricating Oil ◽  
Industrial Equipment ◽  
Monitoring Methods ◽  
Monitoring Technology ◽  
Advantages And Disadvantages ◽  
Scale Particle ◽  
Oil Monitoring

Lubricant failure or irrational lubrication is the root cause of industrial equipment failure. By monitoring the distribution of the suspended particles in lubricants, it is possible to discover hidden lubrication problems. After taking the lubricating oil samples of industrial equipment, the oil monitoring technology is used to analyze the particle size distribution and the type and content of the abrasive particles by electrical, magnetic, and optical monitoring techniques. It is necessary to separate the suspended particles in oils with impurities by some method to eliminate potential safety hazards and ensure the reuse efficiency of the lubricant. In this paper, the principles, advantages, and disadvantages of several important oil monitoring methods are described, and new developments in various methods are analyzed. Several typical methods for separation of the suspended particles in purified oils were introduced. The advantages and disadvantages of each process were summarized. The development direction of lubricant monitoring technology was pointed out, and guidance was provided for the separation and online monitoring of the suspended particles in lubricants. Finally, compared with similar review papers, this paper specifically figured out that ultrasonic separation method has the advantages of real time, high efficiency, and no pollution and has important application value for micron-scale particle separation of large precision machines.

scholarly journals Quantitative Measuring Analysis Method and Mechanism of Wear Particle Settlement

2021 ◽  
Vol 252 ◽  
pp. 03037
Author(s):  
Kaituo Zhang ◽  
Zhiyong Lv
Keyword(s):  
Specific Gravity ◽  
Magnetic Induction ◽  
Wear Particle ◽  
Lubricating Oil ◽  
Precipitation Process ◽  
Wear Particles ◽  
Analysis Method ◽  
Abrasive Particles ◽  
Initial Stage ◽  
Precipitation Analysis

The size and distribution of wear particle in lubricating oil, as important numerical information available in ferrography, is one of the key indexes in wear diagnosis. In this paper, a new method for measuring the size and distribution of abrasive particles is proposed. First, all the abrasive fluid is left standing until all the abrasive particles are precipitated to the bottom. Then, the measuring container is inverted and the whole precipitation process of abrasive particles is recorded by magnetic induction instrument. And according to the precipitation analysis of the wear particle, the following results were obtained:1) At the initial stage of the particle settlement, the gravity, the buoyancy and the drag force of the oil achieve balance quickly, the time and distance of the wear particle moving at a constant velocity can be neglected. 2) The settling velocity is related to the diameter and specific gravity of the wear particle as well as the specific gravity and viscosity of the oil, the distribution of the wear particle is proportional to the square of the diameter of the particle, using the magnetic induction technology, the distribution of particle can be measured by settling time for different sizes of wear particles. 3) Measure the wear particle oil directly, there are different sizes of particles settlement in the bottom at the same time, which causes the difficulty in identifying the size of the particle settlement. The particle should be settled first, and then inverted, settling the particle in accordance with the order from large to small, which facilitates the measurement of different sizes of the particles, different times correspond to different sizes of the particles. 4) The bigger the particle is, the more accurate the measurement and counting is, the smaller the particle is, the bigger the error is.

Oil condition monitoring for HEMM – a case study

2016 ◽  
Vol 68 (6) ◽  
pp. 718-722 ◽  
Author(s):  
Ashwani Kumar ◽  
Subrata Kumar Ghosh
Keyword(s):  
Condition Monitoring ◽  
Mining Industry ◽  
Chemical Properties ◽  
Iron Alloy ◽  
Cylinder Liner ◽  
Wear Particle ◽  
Particle Analysis ◽  
Contamination Level ◽  
Wear Particles ◽  
Content Type

Purpose The paper aims to monitor the condition of heavy Earth-moving machines (HEMMs) used in open cast mines by lube oil analysis. Design/methodology/approach Oil samples at periodic interval were collected from the HEMM engine (Model No: BEML BH50M). Ferrography and Field Emission Scanning Electron Microscopy have been used for the wear particle analysis present in oil samples. Viscosity analysis and Fourier transform infrared spectroscopy have been done to investigate the degradation in quality and changes as compared to the initial structural properties of the lubricants. Findings The results obtained indicates wear in cylinder liner and piston ring. Copper, cast iron, alloy steel and ferrous oxide have been found as rubbing wear particles and cutting wear particles. Contamination level has also been found to be increasing in consecutive older oil samples. Chemical properties degraded with usage time and variations in oxidation and soot level have also been observed in every sample. Practical implications The results will be very much useful to maintenance teams of mining industry for early prediction of any impending failure of the machines, for example, diesel dilution, severe wear of the piston or cylinder liner leading to seizure can be predicted. Originality/value The HEMMs are an important piece of equipment in coal mining. Proper condition monitoring of HEMM is required to reduce the break down and down time to increase production.

scholarly journals A New Transfer Learning Ensemble Model with New Training Methods for Gear Wear Particle Recognition

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
Chunhua Zhao ◽  
zhangwen Lin ◽  
Jinling Tan ◽  
Hengxing Hu ◽  
Qian Li
Keyword(s):  
Transfer Learning ◽  
Wear Particle ◽  
Experimental Results ◽  
The Other ◽  
Particle Identification ◽  
Lubricating Oil ◽  
Support Vector ◽  
Training Methods ◽  
Wear Particles ◽  
Feature Expression

Aiming at solving the acquisition problems of wear particle data of large-modulus gear teeth and few training datasets, an integrated model of LCNNE based on transfer learning is proposed in this paper. Firstly, the wear particles are diagnosed and classified by connecting a new joint loss function and two pretrained models VGG19 and GoogLeNet. Subsequently, the wear particles in gearbox lubricating oil are chosen as the experimental object to make a comparison. Compared with the other four models’ experimental results, the model superiority in wear particle identification and classification is verified. Taking five models as feature extractors and support vector machines as classifiers, the experimental results and comparative analysis reveal that the LCNNE model is better than the other four models because its feature expression ability is stronger than that of the other four models.

Tribology Management and Applications in China Steel

2015 ◽  
Vol 642 ◽  
pp. 168-173
Author(s):  
Yi Sheng Huang
Keyword(s):  
Quality Improvement ◽  
Management System ◽  
Cost Management ◽  
Oil Quality ◽  
Lubricating Oil ◽  
Operating Condition ◽  
Comprehensive Management ◽  
Used Oil ◽  
System Establishment ◽  
Oil Monitoring

Mass amount of equipment and harsh operating condition in steel plants require comprehensive management system, along with lubrication techniques such as lubricating oil quality improvement, used oil monitoring, etc., to ensure proper tribological condition for all mechanical components. In that case, cost management is essential to evaluate the performance of tribology management. This paper is intended to discuss the system establishment, scope of work and actual applications of tribology management in China Steel.

An Experimental Investigation of Industrial Gearbox Condition Using Wear Particle Analysis Technique

2016 ◽  
Author(s):  
Sayed Y. Akl ◽  
Sherif Abd El-Ghafar ◽  
Hamed Mosleh
Keyword(s):  
Condition Monitoring ◽  
Cost Effective ◽  
Wear Particle ◽  
Morphological Data ◽  
Lubricating Oil ◽  
Particle Analysis ◽  
Limit Values ◽  
Wear Particle Analysis ◽  
Analysis Technique ◽  
Wear Modes

In different lubricated machines as engines and gearboxes, the generated wear particles analysis is considered as an effective tool for condition monitoring of these machines. Wear particle analysis as a nondestructive evaluation technique is an effective method to determine the lubricating oil conditions within different lubricated machines, thus monitoring wear modes and imminent failures in these machines. Machine condition monitoring is a cost-effective and reliable system to predict mechanical behavior and efficiency of power plant systems. Qualitative, quantitative and morphological data could be obtained from the wear particle analysis through the periodically taken samples of the lubricant. Different methods are used to detect and analyze wear debris in the lubricant oil, such as ferrograhy, spectrometry, filtergram, particle counters and recently Laser oil analyzer and time-dependent limits monitor factors. The objective of the present work is to apply wear particle analysis technique for condition monitoring of an industrial gearbox transmission over one year period. This transmission belongs to one of the largest carpet manufacturing plant in the world. The chosen gearbox for condition monitoring was a new gearbox installed to the rug textile machine. The gearbox components are elasto-hydrodynamically lubricated with mineral-based oil. The function of the gearbox is to drive the motion (forward and backward) of the knife to cut the fibbers of the carpet during the operation. Periodic oil samples were taken and analyzed through spectrometric technique while selective samples were chosen to be analyzed through ferrography technique. Spectrometric and ferrographic analysis were used where quantitative and qualitative changes in the concentration and size distribution of different particles were analyzed and compared to baseline and limit values. In addition to the sampling process, the gearbox performance was also monitored through measuring the oil temperature that was recorded just after the oil sample intake. The oil temperature is an indication for the gearbox loading which in its turn indicates any failure if it occurs. Results were analyzed, discussed and correlated to the gearbox performance. Also, recommendations were given for better performance based on the investigation and justification of the relevant results.

A Quantitative Model of Wear Loss Based on On-Line Visual Ferrograph

2013 ◽  
Vol 330 ◽  
pp. 338-345
Author(s):  
Chun Hui Wang ◽  
Wei Yuan ◽  
Guang Neng Dong ◽  
Jun Hong Mao
Keyword(s):  
Condition Monitoring ◽  
Testing Machine ◽  
Three Dimensional ◽  
Wear Particle ◽  
Quantitative Model ◽  
Wear Loss ◽  
Wear Particles ◽  
Coverage Area ◽  
Wear Process ◽  
On Line

On-line visual ferrograph (OLVF) is an efficient and real-time condition monitoring device. From the point of flow conservation, on the basis of the particle coverage area data collected by OLVF, this paper deduced two models about wear loss of the tribo-pairs in the wear process, one is general mathematical (GM) model including distribution impact factor of wear particle, and other simplified GM (SGM) model which does not contain the factor. The key factor affecting the accuracy of the two models is the three dimensional information of wear particles referring to particle area and thickness. This model using the disc and the ball whose materials were GCr15 were experimentally demonstrated on a pin-on-disc testing machine. And the OLVF was used to acquire the coverage area of the wear particles, which can reflect the wear loss. It shows that, in some cases, the approximate wear loss in the process was obtained on-line conveniently. Compared with experiment values derived from other wear measurement methods like weighing mass method and surface profilometry method, the SGM model can reflect tendency of wear loss about the tribo-pairs continuously. The deviations about wear loss by the model were discussed. Meanwhile, compared with the traditional means to compute the wear loss, this SGM model could be employed both for off-line analysis and on-line condition monitoring programs.

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